We develop a model of oligopolistic firms that produce partially differentiated products and generate pollution as a byproduct. We analyze and compare two types of pollution regulation: Cap-and-Trade and Taxes. Firms can respond to regulation by any combination of pollution abatement, output reduction, emissions trading (under Cap-and-Trade), or payment of pollution taxes (under Taxes). We prove that well-chosen regulation can, besides reducing pollution, actually improve firms’ profits relative to laissez-faire (unregulated markets), and simultaneously improve consumer surplus and welfare. Thus, regulation Pareto-dominates laissez-faire under a wide range of plausible conditions. These results are driven by an unintended consequence of pollution regulation: Competing firms can use the regulation to tacitly (and credibly) collude to reduce production and improve their profits. We show that the degree of competition plays a critical role in determining the economic consequences of pollution regulation. Our results suggest that the regulator’s primary consideration should be the impact of regulation on consumers rather than producers. This paper was accepted by Vishal Gaur, operations management.

We consider the problem faced by a firm that receives highly differentiated products in an online fashion. The firm needs to price these products to sell them to its customer base. Products are described by vectors of features and the market value of each product is linear in the values of the features. The firm does not initially know the values of the different features, but can learn the values of the features based on whether products were sold at the posted prices in the past. This model is motivated by applications such as online marketplaces, online flash sales, and loan pricing. We first consider a multidimensional version of binary search over polyhedral sets and show that it has a worst-case regret which is exponential in the dimension of the feature space. We then propose a modification of the prior algorithm where uncertainty sets are replaced by their Löwner-John ellipsoids. We show that this algorithm has a worst-case regret which is quadratic in the dimension of the feature space and logarithmic in the time horizon. We also show how to adapt our algorithm to the case where valuations are noisy. Finally, we present computational experiments to illustrate the performance of our algorithm. This paper was accepted by Yinyu Ye, optimization.

We consider the problem of A-B testing when the impact of the treatment is marred by a large number of covariates. Randomization can be highly inefficient in such settings, and thus we consider the problem of optimally allocating test subjects to either treatment with a view to maximizing the precision of our estimate of the treatment effect. Our main contribution is a tractable algorithm for this problem in the online setting, where subjects arrive, and must be assigned, sequentially, with covariates drawn from an elliptical distribution with finite second moment. We further characterize the gain in precision afforded by optimized allocations relative to randomized allocations, and show that this gain grows large as the number of covariates grows. Our dynamic optimization framework admits several generalizations that incorporate important operational constraints such as the consideration of selection bias, budgets on allocations, and endogenous stopping times. In a set of numerical experiments, we demonstrate that our method simultaneously offers better statistical efficiency and less selection bias than state-of-the-art competing biased coin designs. This paper was accepted by Noah Gans, stochastic models and simulation.

Through a controlled two-stage experiment, we explore the performance of solution search strategies to resolve problems of varying complexity. We validate theoretical results that collaborative group structures may search more effectively in problems of low complexity but are outperformed by nominal structures at higher complexity levels. We call into question the dominance of the nominal group technique. Further close examination of search strategies reveals important insights: the number of generated solutions, a typical proxy for good problem-solving performance, does not consistently drive performance benefits across different levels of problem complexity. The average distance of search steps and the problem space coverage also play critical roles. Moreover, their effect is contingent on complexity: a wider variety of solutions is helpful only in complex problems. Overall, we caution management about the limitations of generic, albeit common, rules of thumb, such as “generate as many ideas as possible.” This paper was accepted by Yan Chen, decision analysis.

Temporal distance refers to the time between purchase and consumption in advanced-sales industries. We explore how the response of aggregate demand to price changes with temporal distance in a large, proprietary data set of Florida cruise prices, bookings, and product attributes. We offer the first evidence that cruise demand becomes more sensitive to price during the advance sales period, unlike extant findings in other settings. The results also show that demand is greatest late in the advance sales period, providing the first finding that a late-season high-demand period coincides with a late-season increase in aggregate price sensitivity. The high-demand effect more than offsets the high-price-responsiveness pattern, leading the firm to increase prices throughout the advance sales period. Although the data do not disentangle multiple competing explanations for the main findings, they are large enough to appear in simple data visualizations and robust enough to replicate across many model specifications, parameterizations, and partitions of the data. This paper was accepted by Matthew Shum, marketing.

We study supply chains where multiple suppliers sell to multiple retailers through a wholesale market. In practice, we often observe that both suppliers and retailers tend to influence the wholesale market price that retailers pay to suppliers. However, existing models of supply chain competition do not capture retailers’ influence on the wholesale price (i.e., buyer power) and show that the wholesale price and the order quantity per retailer do not change with the number of retailers. To overcome this limitation, we develop a competition model based on the market game mechanism in which the wholesale price is determined based on both suppliers’ and retailers’ decisions. When taking into account retailers’ buyer power, we obtain the result that is consistent with the observed practice: As the number of retailers increases, each retailer’s buyer power decreases, and each retailer is willing to pay more for her order, so the wholesale price increases. In this case, supply chain expansion to include more retailers (or suppliers) turns out to be more beneficial in terms of supply chain efficiency than what the prior literature shows without considering buyer power. Finally, we analyze the integration of two local supply chains and show that although the profit of the integrated supply chain is greater than the sum of total profits of local supply chains, integration may reduce the total profit of firms in a retailer-oriented supply chain that has more retailers than suppliers. This paper was accepted by Charles Corbett, operations management.

This study examines the effect of audit committee connectedness through director networks on financial reporting quality, specifically the misstatement of annual financial statements. Using network analysis, we examine multiple dimensions of connectedness and find that after controlling for operating performance and corporate governance characteristics, firms with well-connected audit committees are less likely to misstate annual financial statements. In addition, our study demonstrates that audit committee connectedness through director networks moderates the negative effect of board interlocks to misstating firms on financial reporting quality. We conduct several tests to address identification concerns and find similar results. Our findings suggest that firms with better-connected audit committees are less likely to adopt reporting practices that reduce financial reporting quality. This paper was accepted by Suraj Srinivasan, accounting.

The decomposition of dynamic risks a company faces into components associated with various sources of risk, such as financial risks, aggregate economic risks, or industry-specific risk drivers, is of significant relevance in view of risk management and product design, particularly in (life) insurance. Nevertheless, although several decomposition approaches have been proposed, no systematic analysis is available. This paper closes this gap in literature by introducing properties for meaningful risk decompositions and demonstrating that proposed approaches violate at least one of these properties. As an alternative, we propose a novel martingale representation theorem (MRT) decomposition that relies on martingale representation and show that it satisfies all of the properties. We discuss its calculation and present detailed examples illustrating its applicability. This paper was accepted by Baris Ata, stochastic models and simulation.

We investigate the effect of auditing on promoting exports for private firms in emerging markets. Using a sample of private firms from 125 countries between 2006 and 2015, we show that firms that have their financial statements audited have more exports than firms that do not have their financial statements audited. To infer causality, we employ a regression discontinuity design (RDD). Using the discontinuity around the mandatory financial audit threshold, we find that firms slightly above the threshold have more exports than do firms that are slightly below the threshold. We also exploit the countries with exogenous regulation shocks to the mandatory audits. Using the difference-in-differences (DiD) design, we find that firms that are exempted from mandatory audits have less exports subsequent to the regulation change. Further analyses reveal that the effect of auditing is more pronounced in countries with higher audit quality and for firms with limited alternative information. Our findings suggest that the auditing function promotes exports—an important economic consequence for the global economic development. This paper was accepted by Shivaram Rajgopal, accounting.